Text Classification
Transformers
Safetensors
English
me2bert
feature-extraction
Moral Foundation Prediction
MFT
Morality
Morality Values
BERTForMoralPrediction
Emotions
Events
https://aclanthology.org/2025.coling-main.638.pdf
custom_code
Instructions to use lorenzozan/ME2-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lorenzozan/ME2-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lorenzozan/ME2-BERT", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lorenzozan/ME2-BERT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from lorenzozan/ME2-BERT: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/lorenzozan/ME2-BERT/resolve/main/tokenizer.json
- Command line
-
hf download hf://lorenzozan/ME2-BERT/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/lorenzozan/ME2-BERT/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.